Clojure: Transducers

Transducers work even better with a Clojure library called Injest. It has macros similar to the standard Clojure threading macros except Injest’s macros will recognize when you’re using transducers and automatically compose them correctly. You can even mix and match transducers and non-transducer functions and Injest will do its best to optimize the sequence of operations. And wait, there’s more! Injest has a parallelizing macro that will use transducers with the Clojure reducers library for simple and easy use of all your cores. Get it here: https://github.com/johnmn3/injest

Note: I’m not the author of Injest, just a satisfied programmer.

I made srfi-171 [0], transducers for scheme. If you have any questions about them in general I can probably answer them. My version is pretty similar to the clojure version judging by the talks Rich Hickey gave on them.

I know a lot of people find them confusing.

0: https://srfi.schemers.org/srfi-171/srfi-171.html

Transducers are IMHO one of the most under-appreciated features of Clojure. Once you get to know them, building transducer pipelines becomes second nature. Then you realize that a lot of data processing can be expressed as a pipeline of transformations, and you end up with reusable components that can be applied in any context.

The fact that transducers are fast (you don't incur the cost of handling intermediate data structures, nor the GC costs afterwards) is icing on the cake at this point.

Much of the code I write begins with (into ...).

And in Clojure, like with anything that has been added to the language, anything related to transducers is a first-class citizen, so you can reasonably expect library functions to have all the additional arities.

[but don't try to write stateful transducers until you feel really comfortable with the concepts, they are really tricky and hard to get right]

May I offer a little code riff slicing FizzBuzz using transducers, as one would do in practice, in real code (as in not a screening interview round).

Demo One: Computation and Output format pulled apart

  (def natural-nums (rest (range)))

  (def fizz-buzz-xform
    (comp (map basic-buzz)
          (take 100))) ;; early termination

  (transduce fizz-buzz-xform ;; calculate each step
             conj ;; and use this output method
             []   ;; to pour output into this data structure
             natural-nums)

  (transduce fizz-buzz-xform ;; calculate each step
             str ;; and use this output method
             ""  ;; to catenate output into this string
             natural-nums) ;; given this input

  (defn suffix-comma  [s]  (str s ","))

  (transduce (comp fizz-buzz-xform
                   (map suffix-comma)) ;; calculate each step
             str ;; and use this output method
             ""  ;; to catenate output into this string
             natural-nums) ;; given this input

(edit: fix formatting, and kill dangling paren)

Nowadays you can make use of some transducers ideas via gatherers in Java, however it isn't as straightforward as in plain Clojure.

When I first read about transducers I was wowed. For example, if I want to walk all the files on my computer and find the duplicate photos in the whole file system, transducers provide a conveyor belt approach. And whether there are saving in terms of memory or anything, maybe. But the big win for me was to think about the problem as pipes instead of loops. And then if you could add conditionals and branches it is even easier to think about. At least I find it so.

I tried to implement transducers in JavaScript using yield and generators and that worked. That was before async/await, but now you can just `await readdir("/"); I'm unclear as to whether transducers offer significant advantages over async/await?

[[Note: I have a personal grudge against Java and since Clojure requires Java I just find myself unable to go down that road]]

Is there a gain of clojure transducers to js style iterators? - https://developer.mozilla.org/en-US/docs/Web/JavaScript/Refe...

https://developer.mozilla.org/en-US/docs/Web/JavaScript/Refe...

both solve the copying problem, and not relying on concrete types

I never understood what was so special about Clojure's Transducers. Isn't it essentially just applying a transformation on the lambda applied to a fold?

its Common Lisp cousin: https://github.com/fosskers/transducers/

From (2016) at least.

https://web.archive.org/web/20161219045343/https://clojure.o...

The key insight behind transducers is that a ton of performance is lost not to bad algorithms or slow interpreters but to copying things around needlessly in memory, specifically through intermediate collections.

While the mechanics of transducers are interesting the bottom line is they allow you to fuse functions and basic conditional logic together in such a way that you transform a collection exactly once instead of n times, meaning new allocation happens only once. Once you start using them you begin to see intermediate collections everywhere.

Of course, in any language you can theoretically do everything in one hyperoptimized loop; transducers get you this loop without much of a compromise on keeping your program broken into simple, composable parts where intent is very clear. In fact your code ends up looking nearly identical (especially once you learn about eductions… cough).

I am a fan of Christophe Grand's xforms library -- https://github.com/cgrand/xforms -- I find the transducer nexus function, by-key, to be particularly useful for eliminating clojure.core destructuring dances when one needs group-by with post-processing.

transducers and async flow are :chefkiss

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You get this for free in Haskell, and you also save on not having to remember useless terminology for something that has no application on their own outside Foldables anyways.